Statistical reverse engineering methods for high-throughput molecular data
With the recent advancement in the high-throughput technologies, molecular biology is rapidly evolving into a quantitative science. This achievement led to an increased role of reverse engineering methods in making sense of this high-dimensional data. The development and application of such methods will guide new experiments, shed new light on existing hypotheses and will eventually trigger new discoveries that have been difficult to achieve using the traditional biochemical approaches alone. This special issue will focus on statistical reverse engineering methods for high-throughput molecular data.
Edited by: Heinz Koeppl, Maria Rodriguez Martinez and Nurgazy Sulaimanov